[BioC] adjPval and qvalue
James W. MacDonald
jmacdon at med.umich.edu
Tue Mar 21 15:21:41 CET 2006
sabrina.shao wrote:
> Hello, all
> I am confused by the adjPval from maanova and qvalue. I am not sure
> after I use the matest , which one I should use if I want to take a look
> at the FDR. Should I compute the q-values of these adjusted P-values or
> just use the original p-values to compute the corresponding q-values. Or
> I have some misunderstanding about q-values and adjusted pvalues. Thanks
I think you are confused. The matest() function doesn't compute adjusted
p-values. It computes permuted p-values which is a different thing.
Anyway, the example for adjPval() pretty much outlines the steps you
should be taking:
data(paigen)
paigen <- createData(paigen.raw, n.rep=2)
model.noint.fix <- makeModel(data=paigen,
formula=~Array+Dye+Spot+Strain+Diet)
# F-test strain effect
## Not run:
test.strain.fix <- matest(paigen, model.noint.fix, term="Strain",
n.perm=100,
shuffle.method="resid", test.method=rep(1,4))
# make FDR adjusted P values
test.strain.fix <- adjPval(test.strain.fix)
## End(Not run)
# there will be new fields in test.strain.fix after this
Best,
Jim
>
> Sabrina
>
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--
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623
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